Understanding and counteracting biodiversity losses requires quantitative knowledge on species distribution and abundance across space and time, as well as integrated and interoperable information on climate conditions and climatic changes. In this paper we developed a new biodiversity-climate database for Italy, ClimCKmap, based on the critical analysis, quality estimation and subsequent integration of the CKmap database with several high-resolution climate datasets. The original database was quality-checked for errors in toponym, species name and dating; the retained records were georeferenced and their distribution polygonised via Voronoi tessellation. We then integrated the species distribution information with several high-resolution climatic datasets: average monthly minimum and maximum temperature and total monthly precipitation were reconstructed for each Voronoi cell and year. The resulting database contains 268,977 occurrence records from 8,445 binomials and 16,332 localities, dating between 1680 and 2006 CE. This dataset, fully available at https://doi.org/10.6084/m9.figshare.7906739.v4 and http://hdl.handle.net/21.11125/a91f85cb-befd-4e14-8e83-24f17c4a0491 , represents the largest, fully quality-checked, spatially, temporally and climatically explicit distribution database ever assembled for the Italian fauna, now ready for scientific exploitation.

ClimCKmap, a spatially, temporally and climatically explicit distribution database for the Italian fauna

Marta S;Brunetti M;Amori G;Provenzale A
2019

Abstract

Understanding and counteracting biodiversity losses requires quantitative knowledge on species distribution and abundance across space and time, as well as integrated and interoperable information on climate conditions and climatic changes. In this paper we developed a new biodiversity-climate database for Italy, ClimCKmap, based on the critical analysis, quality estimation and subsequent integration of the CKmap database with several high-resolution climate datasets. The original database was quality-checked for errors in toponym, species name and dating; the retained records were georeferenced and their distribution polygonised via Voronoi tessellation. We then integrated the species distribution information with several high-resolution climatic datasets: average monthly minimum and maximum temperature and total monthly precipitation were reconstructed for each Voronoi cell and year. The resulting database contains 268,977 occurrence records from 8,445 binomials and 16,332 localities, dating between 1680 and 2006 CE. This dataset, fully available at https://doi.org/10.6084/m9.figshare.7906739.v4 and http://hdl.handle.net/21.11125/a91f85cb-befd-4e14-8e83-24f17c4a0491 , represents the largest, fully quality-checked, spatially, temporally and climatically explicit distribution database ever assembled for the Italian fauna, now ready for scientific exploitation.
2019
Istituto di Geoscienze e Georisorse - IGG - Sede Pisa
Istituto di Scienze dell'Atmosfera e del Clima - ISAC
Istituto per lo Studio degli Ecosistemi - ISE - Sede Verbania
Istituto di Ricerca sugli Ecosistemi Terrestri - IRET - Sede Secondaria Montelibretti
Italian fauna,
climate,
database,
geographical sampling bias,
species richness,
climate surfaces,
big data,
temperature,
precipitation,
collections,
world
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/393415
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